Risk Analysis, Routing And Network Optimization For Hazmats Transportation By Road Under Uncertain Condition

Hazardous materials are industrial raw material, energy resources and products and indispensable to our modern society. Most hazardous materials are not used at their point of production, they are transported over considerable distances, and their road freight volumes are high. However, incidents involving hazardous materials cargo can lead to severe consequences characterized by fatalities, injuries, evacuation, property damage, environmental degradation, and traffic disruption. So, risk control and safety guarantee of hazardous materials transportation have aroused people's considerable attention. And the path selection, network design, and emergency response facility location for hazardous materials transportation under uncertain conditions are important means for the transportation safety.The theoretical framework of path selection, network design, and emergency response facility location for hazardous materials transportation is constructed in this dissertation, in order to provide theoretical support for hazardous materials transportation decision problems. The contributions of this dissertation include:(1) The existing literatures on risk measurement and risk analysis are reviewed, and the existing problems are discovered.According to the existing research achievements, stochastic theory and fuzzy logic are presented to assess the risk of hazardous materials transportation. The nonprarametric kernel density estimation is applied to estimate the probability density distributions of that accident rates, and probability-possibility transformation method is introduced to obtain the fuzzy numbers of risk parameters.Based on the advantages of the Bayesian method integrating prior information sample information, Bayesian method is presented to assess the risk parameters of hazardous materials transportation. The prior distributions of random variables are determined by historical data and expert knowledge, and the risk parameters such as accident frequency are assessed with given new sample information.Rough set theory is introduced and it's applicability to risk analysis of hazardous materials transportation is discussed. Main factors and secondary factors affecting the incident occurrence are distinguished with attribute significance method of rough set theory. And the relations between factors and incidents are revealed with the rule reasoning method of rough set theory.(2) Based on the existing simple accumulation formula and the assumption that the link attributes follow normal distributions and lognormal distribution respectively, the recurrence formula of the probability density distributions for route attributes such as route risk and route travel time are developed. Considering the probability density distributions for route attributes, the time windows constraints and route attribute reliability constraints, the nondominated paths are achieved by means of three dominance criteria. As for the case where the mutual restriction of urban development and hazardous materials transportation exist, the maximal amount of hazardous materials that are allowed to be transported on each road link can be achieved by individual risk and societal risk threshold. Ulteriorly, according to the freight volume limitations, the algorithm of the minimum-cost maximum flow is used to achieve the optimal flow distribution solutions.(3) The traveling salesman problem is applied to solve the hazardous materials distribution problem. The convolution-propagation formulas of means and variances for the route attribute distributions are analyzed and then the convolution-propagation formulas for route risk distributions considering both traveling risk and service risk are deduced. In order to solve the stochastic dynamic hazardous materials distribution problem, the algorithm presented by Tsung-Sheng Chang is improved and a new heuristic algorithm is developed. As for complicated environments with multi-vehicle and multi-goods, the vehicle routing problem model is used.(4) In a real-life transportation network, the transportation risk and cost of each road link are random variables and follow certain distributions. A stochastic bi-level programming model for network design is developed, which takes into account the interaction between the traffic manages and the hazardous materials transportation carriers. A genetic algorithm based on simulation is designed to solve the problem and a numerical example is presented. Base on graph theory and uncertain programming theory, a minimum risk tree model with uncertainty for hazardous materials transportation is developed. In the first phase the minimum risk tree is found and in the second phase the tree network is extended by adding links, which reduces the total cost and increases risk not rapidly and satisfactory solutions can be achieved.(5) Based on the assumption of lognormal distributions of response times, an optimization model for emergency response facility location is developed, which takes into account response time uncertainty, the number of the people exposed to the danger, the incident probability, the equal workload constraints, and the response time constraints. The objective function is to maximize the total expected demand covered, and the decision variables are the selected location sites and the respective response facilities for every demand nodes. In order to meet the real-life need of emergency response facility locations, a maximal arc-covering model is used and extended with partial coverage and gradual covering decay, and then a maximal arc-covering model with gradual covering decay is developed for emergency response facility location.